Add a column with incremental values in Pandas dataFrame

In this article, we will discuss different ways to add a new column in DataFrame with incremental values or numbers.

Table Of Contents

Preparing DataSet

First we will create a DataFrame from list of tuples i.e.

import pandas as pd

# List of Tuples
employees= [('Mark', 'US', 'Tech',   5),
            ('Riti', 'India', 'Tech' ,   7),
            ('Shanky', 'India', 'PMO' ,   2),
            ('Shreya', 'India', 'Design' ,   2),
            ('Aadi', 'US', 'Tech', 11),
            ('Sim', 'US', 'Tech', 4)]

# Create a DataFrame object from list of tuples
df = pd.DataFrame(employees,
                  columns=['Name', 'Location', 'Team', 'Experience'])
print(df)

Output:

     Name Location    Team  Experience
0    Mark       US    Tech           5
1    Riti    India    Tech           7
2  Shanky    India     PMO           2
3  Shreya    India  Design           2
4    Aadi       US    Tech          11
5     Sim       US    Tech           4

Now, suppose we want to add a new column in this DataFrame ‘Age’, and this column should contain incremental values like 31, 32, 33, 34, 35 etc. Let’s see how to do that.

Add new column with incremental values in Pandas DataFrame

We can call the range() function of Python, to give a range of numbers from start till end. Like, start will be 30 in our case, and end will be 30 + N. Where, N is the number of rows in the DataFrame. So, it will return a sequence of numbers from 31 till 31 + N. Then we can add this squence as a new column in the DataFrame. Let’s see an example,

start = 30

# Add column with incremental values from 30 onwards
df['Age'] = range(start, start + df.shape[0])

print(df)

Output:

     Name Location    Team  Experience  Age
0    Mark       US    Tech           5   30
1    Riti    India    Tech           7   31
2  Shanky    India     PMO           2   32
3  Shreya    India  Design           2   33
4    Aadi       US    Tech          11   34
5     Sim       US    Tech           4   35

Here, we added a new column ‘Age’ in the DataFrame with incremental values.

Add new DataFrame column with incremental values of equal interval

Suppose we want to a add a new column containing incremental values. But the adjacent values should separated by a given step size. We can do that using the range() function. Let’s see the example,

# Add column with incremental values from 30 onwards
# with step size 5
df['Age'] = range(start, start + (5 * df.shape[0]), 5)

print(df)

Output:

     Name Location    Team  Experience  Age
0    Mark       US    Tech           5   30
1    Riti    India    Tech           7   35
2  Shanky    India     PMO           2   40
3  Shreya    India  Design           2   45
4    Aadi       US    Tech          11   50
5     Sim       US    Tech           4   55

Here, we added a new column ‘Age’ in the DataFrame with incremental values, but each value in this column is greater than previous value by 5.

Summary

Today, we saw how to add a new column in DataFrame with incremental values. Thanks.